In my second post, I will go over how to make a shaded choropleth map of the U.S. using Leaflet.
#For this runthrough, I am using NYT's nationwide COVID case data by state to produce a choropleth map that documents the amount of deaths per state by February 22 of this year.
#Before starting, I loaded the following packages
library(tidyverse)
library(lubridate)
library(readxl)
library(janitor)
library(glue)
library(leaflet)
library(RColorBrewer)
library(htmlwidgets)
library(htmltools)
library(tigris)
library(tmap)
library(tmaptools)
#First, I imported the NYT's covid case data for states
covidcases <- read_csv("https://raw.githubusercontent.com/nytimes/covid-19-data/master/us-states.csv")
#I also downloaded the polygon boundaries for states at the lowest resolution using the tigris package.
states <- tigris::states(cb=T)
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|============================================================| 100%#After reading the csv as "covidcases" and saving the tigris data as "states", I filtered out the covid cases data to just account for data on Feb 22 and selected the columns of state and deaths to group together. I saved this new dataset as "covidfeb22deaths".
covidfeb22deaths <- subset(covidcases, date == "2021-02-22", select=c(state, deaths))
#Then, I joined together the data from "states" and "covidfeb22deaths" using the function geo_join, naming the joint data "feb22states". I indicated that the two datasets should be joined by the columns "NAME" (in states) and "state" (in covidfeb22deaths.)
feb22states <- geo_join(states, covidfeb22deaths, by_sp = "NAME", by_df = "state")
#I specified bin values here to categorize states based on their number of deaths on Feb 22.
bins <- c(0, 100, 500, 1000, 5000, 10000, 50000, 100000, Inf)
#And I created a color palette with the colors of yellow, orange, and red to link together my bin values with the number of deaths each state had.
pal <- colorBin("YlOrRd", domain = states$deaths, bins = bins)
#Now onto making the choropleth - I decided to use the Leaflet package to do this. I saved this map as "covidmap", and added the functions needed to pull the data from "feb22states" to a choropleth map of the U.S. I set the view and zoom to see the whole country of the U.S., and used the addPolygons function to set the characteristics of color appearance on the map. I also added a legend on the bottom right corner to indicate what death values each color represents, using the addLegend function.
covidmap <- leaflet(data=feb22states) %>%
addTiles() %>%
setView(-98.483330, 38.712046, zoom = 4) %>%
addPolygons(data = feb22states, stroke = TRUE,
fillColor = ~pal(deaths),
color = "white",
weight = 2,
opacity = 1,
fillOpacity = 0.8,
dashArray = "3") %>%
addLegend(pal = pal,
values = feb22states,
bins = 9,
position = "bottomright",
title = "Total Deaths",
labFormat = labelFormat(digits = 0))
#Check out the finished product!
covidmap
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For attribution, please cite this work as
Edralin (2021, April 19). Francesca's Blog: Making a Shaded Choropleth Map Using Leaflet. Retrieved from https://francescaedralin.netlify.app/posts/2021-04-19-my-second-post/
BibTeX citation
@misc{edralin2021making,
author = {Edralin, Francesca},
title = {Francesca's Blog: Making a Shaded Choropleth Map Using Leaflet},
url = {https://francescaedralin.netlify.app/posts/2021-04-19-my-second-post/},
year = {2021}
}